Identification of Bacterial Fish Pathogens in Brazil by Direct Colony PCR and 16S Rrna Gene Sequencing

Advances in Microbiology, 2015, 5, 409-424 Published Online June 2015 in SciRes. http://www.scirp.org/journal/aim http://dx.doi.org/10.4236/aim.2015.56042

Identification of Bacterial Fish Pathogens in Brazil by Direct Colony PCR and 16S rRNA Gene Sequencing

F. A. Sebastião, L. R. Furlan, D. T. Hashimoto, F. Pilarski* Aquaculture Center of São Paulo State University—CAUNESP, Universidade Estadual Paulista, Jaboticabal, Brazil Email: *[email protected]

Received 14 May 2015; accepted 11 June 2015; published 16 June 2015

Copyright © 2015 by authors and Scientific Research Publishing Inc. This work is licensed under the Creative Commons Attribution-NonCommercial International License (CC BY-NC). http://creativecommons.org/licenses/by-nc/4.0/

Abstract Intensive fish farming systems in Brazil have increased the disease incidence, mainly of bacterial origin, due to higher stocking density, high organic matter levels and poor quality of the aquatic environment that causes high mortality rates during outbreaks. The identification of pathogenic species using a fast and reliable method of diagnosis is essential for successful epidemiological studies and disease control. The present study evaluated the use of direct colony PCR in combina- tion with 16S rRNA gene sequencing to diagnose fish bacterial diseases, with the goal of reducing the costs and time necessary for bacterial identification. The method was successful for all 178 isolates tested and produced bands with the same intensity as the standard PCR performed using pure DNA. In conclusion, the genetics methods allowed detecting the most common and important pathogens in Aquaculture, including 12 species of occurrence in Brazilian fish farms. The results of the present study constitute an advance in the available diagnostic methods for bacterial pathogens in fish farms.

Keywords Direct Colony PCR, 16S rRNA Sequencing, Bacterial Fish Pathogens

1. Introduction Due to its high water availability and favorable climate conditions, Brazil displays high potential for the development of fish farming, which is an activity that has been growing substantially over the last few years. Ac-

*Corresponding author.

How to cite this paper: Sebastião, F.A., Furlan, L.R., Hashimoto, D.T. and Pilarski, F. (2015) Identification of Bacterial Fish Pathogens in Brazil by Direct Colony PCR and 16S rRNA Gene Sequencing. Advances in Microbiology, 5, 409-424. http://dx.doi.org/10.4236/aim.2015.56042

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cording to the Food and Agriculture Organization of the United Nations [1], Brazil is the second largest aquaculture producer in Latin America and the Caribbean, and freshwater aquaculture (tilapia, carp, and native fish) represented 87% (545,300 ton) of the total aquaculture production in 2011. The growing interest in this activity and, consequently, the search for higher profitability, have been leading producers to adopt super-intensive production systems. However, the high density of confined fish, inadequate farming management practices, and water contamination by toxic products cause chronic stress and immuno- suppression in farmed animals. These effects lead to the occurrence of diseases and epizootic outbreaks caused by pathogens that would not have high expression in natural environments [2]. Knowledge about the etiological agents, pathogenesis, biochemistry, antigenicity, epizootiology, and inter-relationship of stress and environmental factors of bacterial infections affecting fish is essential to avoid and control diseases. However, these factors have not been well studied, especially because fish farming is a recent activity, with its intensification beginning in the 1990s [3]. Gram-negative bacteria such as Aeromonas, Flavobacterium, Pseudomonas, and Francisella and gram-positive bacteria from the genera Streptococcus and Lactococcus [4]-[11] are some of the pathogens responsible for economic losses in Brazil. They can cause high fish mortality rates up to 72 h after infection [12]. Although the number of studies focusing on the diagnosis of bacterial etiological agents has increased over the last few years, there are still few available alternatives for the control of fish bacterial infections in Brazil. Therefore, quicker and more effective diagnostic alternatives are necessary, which would help control diseases before they lead to irreversible clinical consequences and high mortality rates. Molecular diagnostic methods use reduced volumes of sample material and exhibit high sensitivity, specificity, and accuracy in pathogen detection [13]. Methods that do not require purified DNA extraction, such as direct colony PCR, are quicker and less expensive and may greatly aid in the early detection of fish pathogens [14]. In addition, because not all microorganism sequences are catalogued in current databases, the use of universal and degenerate primers is a wise strategy. For this reason, methods based on 16S rRNA ribosomal gene amplification and sequencing have been widely ex- plored [13]. The use of universal PCR primers is based on the hypothesis that the primers used are complementary to con- served regions of genes in the environment, resulting in amplification; in turn, heterogeneity is found inside of the fragments flanked by the primers, in hypervariable regions [15] [16]. This method has been revolutionizing microbial ecology, from studies of non-cultivable bacteria to the correct identification of pathogens for accurate diagnoses. The aim of the present study was to evaluate the direct colony PCR combined with 16S rRNA gene sequencing as a faster and less expensive method to identify fish bacterial pathogens, compared to the classic PCR protocol. Moreover, we have used these methods to demonstrate the efficiency of genetic approaches for the practical evaluation of the diagnosis of aquaculture diseases in Brazilian fish farms.

2. Materials and Methods 2.1. Bacterial Strains and Culture Conditions 178 bacterial isolates were obtained between 2010 and 2014 from the following hosts (n = number of assessed fish): tilapia (Oreochromis niloticus n = 93), tambaqui (Colossoma macropomum n = 10), carp (Cyprinus carpio n = 3), cachara (Pseudoplatystoma reticulatum n = 34), and pacu (Piaractus mesopotamicus n = 8). The hosts exhibited clinical signs of bacterial diseases, such as skin ulcerative lesions, hemorrhagic septicemia, meningoencephalitis, fin rot, exophthalmia, and were collected at fish farms in different regions of Bra- zil:Dourados (Mato Grosso do Sul State, 22˚13'16"S, 54˚48'20"W, n = 38), Rio de Janeiro (Rio de Janeiro State, 22˚54'S, 43˚10'W, n = 4), Itambaracá (Paraná State, 23˚0'49"S, 50˚24'7"W, n = 10), Itaju (22˚25'37''S, 45˚27'11''W), Arealva (22˚1'38''S, 48˚54'36''W), Porto Ferreira (21˚51’18’’S, 47˚28'45''W), Guaíra (20˚19'5''S, 48˚18'42''W), Santa Fé do Sul (20˚12'43''S, 50˚55'38''W), Palmital (22˚47'30''S, 50˚12'18''W) and Jaboticabal (21˚15'19''S, 48˚19'21''W—São Paulo State, n = 123). For the isolation of bacteria, scrapings were performed using sterile swabs on fish kidneys and brain. Gram- negative colonies were plated on TSA (Tryptic Soy Agar-Biolife), and TSB (Tryptic Soy Broth-Biolife) and incubated for 24 h in bacteriological incubator adjusted to 28˚C. While gram-positive colonies were seeded in Columbia blood agar (Difco) incubated for 24 - 72 h at 30˚C and subcultured in BHI (Brain Heart Infusion

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Broth, Himedia). The strains of Palmital (SP) were obtained directly from the Laboratory of Aquatic Animal Disease, APTA, Votuporanga, SP.

2.2. Molecular Identification of Isolates Two methods of molecular diagnosis were compared in this study aiming to evaluate the efficiency of direct colony PCR (time and cost effectiveness) in relation to the PCR amplification of purified DNA by extraction, both combined with gene sequencing (Table 1). The standard PCR of purified DNA method followed the steps below.

2.2.1. DNA Extraction One colony of each isolated was transferred to a tube containing appropriate liquid culture medium (TSB for gram-negative and BHI for gram-positive) and incubated at 28˚C until the OD600 was between 1 and 1.5. Fol- lowing incubation, 1.0 mL of the bacteria culture was centrifuged at 12,000×g for 1 min, the supernatant was discarded, and the pellet was frozen at −20˚C until DNA extraction. The Axyprep® miniprep kit for bacterial genomic DNA was used according to the manufacturer’s instructions (Axygen Biosciences, Union City, CA, USA). DNA was quantified by fluorometry using a Qubit 2.0 fluorometer (Life Technologies, NY, USA).

2.2.2. Standard PCR PCR was performed in a 25 µL final volume, containing 2.5 µL of 10X buffer (10 mM Tris-HCl, 50 mM KCl), 0.2 µL of 25 mM dNTP, 1.0 µL of 50 mM MgSO4, 0.2 µL of Taq High Fidelity (Platinum®Taq DNA Polyme- rase, Life Technologies, NY, USA), 2.0 µL of each primer (10 pmol), 25 ng of DNA template, and Milli-Q water up to the final volume. The PCR program consisted of 94˚C for 2 min; 35 cycles of 94˚C for 30 seconds, 55˚C for 30 s, and 68˚C for 1.5 min; and final extension at 68˚C for 10 min. We used the primers 8F/907R (Table 2), specific for the 16S rRNA bacterial gene [15] [17] [18]. The resulting amplicons of approximately 900 bp (base pair) were analyzed by electrophoresis in 1.5% agarose gel stained with ethidium bromide, according to Sambrook et at. [19].

2.2.3. Purification of PCR Products and Gene Sequencing PCR products were purified using a MinElute Kit (Qiagen, Crawley, West Sussex, UK) according to the manufacturer’s instructions. Purified PCR products were quantified using a Qubit 2.0 fluorometer, and gene sequencing was performed using 50 ng/µL per sample. Sequencing was performed according to Sanger [20]. PCR products were amplified using AmpliTaq polymerase and BigDye Terminator (Applied Biosystems) according to the manufacturer’s instructions, using the primer 907R. Sequencing was performed using an ABI PRISM 3730 DNA analyzer (Applied Biosystems).

Table 1. Steps of the two methods compared in this study: Standard PCR of purified DNA and direct colony PCR, both combined with the 16S rRNA gene sequencing.

Steps Standard PCR Direct colony PCR

Bacterial isolation X X

Replication in broth X -

DNA extraction X -

PCR X X

Electrophoresis X X

PCR product purification X -

16S rRNA sequencing X X

Nucleotide analysis X X

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Table 2. Sequence of primers used for amplification of the 16S rRNA gene.

Primer Target sequence 5’- 3’

8F AGA GTT TGA TYM TGG CTC AG

907R CCG TCA ATT CMT TTR AGT TT

2.3. Direct Colony PCR This method allows PCR to be performed on colonies isolated from Petri dishes, without the step of DNA extraction. Colonies (1 - 2 mm diameter) were inoculated by placing a sterile tooth pick at the bottom of a PCR tube (0.2 mL) and incubated at −20˚C overnight. The following solution was then added in the PCR tube: 2.0 µL of 10× buffer (10 mM Tris-HCl, 50 mM KCl), 1.2 µL of 50 mM MgCl2, 0.2 µL of 25 mM dNTP, 0.7 µL of each primer 8F/907R (10 pmol/µL), 0.2 µL of Taq DNA polymerase (2.5 U), and Milli-Q water up to 20 µL. The PCR program consisted of 95˚C for 5 min; 30 cycles of 95˚C for 1 min, 54˚C for 1.5 min, and 72˚C for 1 min; and final extension at 72˚C for 5 min. The amplified PCR products, at 50 ng/µL mean concentration, were analyzed by electrophoresis in a 1.5% agarose gel stained with ethidium bromide [19]. The gels were visualized under UV light, using a ChemiDoc MP imaging system (Bio-Rad). Samples were quantified by fluorometry using a Qubit 2.0 fluorometer and sequenced as described above. After sequencing, samples of both methods had their nucleotides analyzed.

2.4. Analysis of Nucleotide Sequences The obtained sequences were visualized using the Bio Edit Sequence Alignment Editor software (v. 7.1.11). Phred quality of sequences was determined. The initial and final portions of the sequences were then removed, keeping only the high-quality fragment. After trim, sequences were exported in FASTA format and compared with the GenBank database (http://www.ncbi.nlm.nih.gov/genbank/) using the Eztaxon algorithm (http://www.ezbiocloud.net/eztaxon/identify). 100% coverage and identity ≥ 98% were considered for specific identification. Sequences were also submitted to Ribosomal Database Project II (http://rdp.cme.msu.edu) for comparison and identification. The sequences obtained in the present study were deposited at NCBI GenBank under accession numbers KJ560937 to KJ561113. The complete list of species identified, accession numbers, place of origin, fish species, season and year of collection, and size of amplified PCR products were included as Supplementary Material. The Brazilian isolates tested were S. agalactiae (n = 23), S. iniae (n = 4), Lactococcus lactis (n = 11), L. raffinolactis (n = 2), L. garvieae (n = 16), Enterococcus casseliflavus (n = 16), E. durans (n = 2), E. faecalis (n = 11), Edwardsiella tarda (n = 5), Aeromonas hydrophila (n = 16), A. jandaei (n = 2), A. veronii (n = 15), Pseu- domonas sp. (n = 15). A phylogenetic diagram was constructed for validation of the sequencing data, using the 138 isolates listed above from the 178 of the present study. In addition, we used as reference 16 sequences originated from different countries (Table 3), obtained from GenBank database. The 154 FASTA sequences were aligned using the ClustalW Multiple Alignment tool (BioEdit Sequence Alignment Editor software, v. 7.1.11). The data were then entered in Mega software (v. 5.05) to determine the best substitution model. As a result of the preliminary analysis, a maximum-likelihood phylogenetic diagram was constructed, using the Kimura 2-parameter model, with a gamma-shape parameter with 5 categories, the nearest-neighbor-interchange tree inference option. The stability of internal nodes was assessed by bootstrap analysis with 1000 replicates.

3. Results and Discussion 3.1. The Comparison of the Two Methods: Direct Colony PCR and Classic PCR Protocol We found no difference in the band size in agarose electrophoresis, nor in the peaks pattern of electropherograms in the two methods evaluated. Bands resulting from the direct colony PCR exhibited the same intensity as those of the standard PCR of purified DNA, for all 178 isolates tested (Figure 1).

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Figure 1. Electropherogram of 1.5% agarose gel stained with ethidium bromide, showing amplification of 16S rRNA gene (primers 8F/907R). Lane 1, Marker 1kb. Lane 2, direct colony PCR. Lane 3, standard PCR. Lane 4, negative control.

Table 3. Reference strains used for the maximum-likelihood phylogenetic analysis and their places of origin.

Genbank access number Identification Origin

JX861241 Aeromonas veronii India

ATCC35624 Aeromonas veronii Japan

NR_074841 Aeromonas hydrophila USA

JN644061 Aeromonas jandaei China

ATCC49568 Aeromonas jandaei India

NBRC_105688 Edwardsiella tarda Japan

EU239205 Pseudomonas fulva Korea

KC210866 Enterococcus casseliflavus China

AB530699 Enterococcus faecalis Thailand

NR_036922 Enterococcus durans Germany

KC176716 Streptococcus agalactiae China

NR_027517 Streptococcus dysgalactiae Japan

NR_025148 Streptococcus iniae Israel

NR_044359 Lactococcus raffinolactis South Korea

KC429785 Lactococcus lactis China

ATCC49156 Lactococcus garvieae USA

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Electropherograms resulting from the sequencing of both methods exhibited Phred quality scores ≥20. All the isolates had the same results of bacterial identification for both techniques (direct colony PCR and standard PCR of purified DNA). Thus, direct colony PCR was a less expensive and faster diagnostic method, as shown on Ta- ble 4. There were 51% savings in cost analysis per sample for direct colony PCR compared to Standard PCR of purified DNA. Moreover, direct colony PCR reduces 2 days in time to issue the final report. After the installa- tion of a bacterial outbreak, fish shoals can be decimated by up to 72 hours. Therefore, rapid diagnosis in aquaculture is a critical point in the production chain, which can be assessed by the genetic tools of the present study. A faster diagnosis is important, since the one based on classical microbiology techniques (isolation, platting and biochemical tests) can exceed the time for treatment in seven to 15 days and, in many cases, ending up inconclusive. The molecular diagnosis, on the other hand, can provide a faster, low cost, conclusive diagnosis, which is essential to determine the best treatment in fish farming (Table 5). Besides, in an attempt to control disease outbreaks, in classical scenery in Brazil, producers use multiple anti- biotics indiscriminately, selecting resistant strains, contaminating fish, water and raising the risks to consumer health, endorsing the need for rapid and effective diagnosis [21]. A maximum-likelihood phylogenetic tree was built to validate the sequencing data (Figure 2). The bacterial isolates of the same species or phylogenetic related were correctly grouped into a common branch, as expected. The principle of maximum likelihood for phylogenetic inference evaluates the probability of a given model of evolutionary changes explaining the origin of the data observed. In this method, the initial tree is constructed using the neighbor-joining method, and the length of each branch is adjusted to maximize the likelihood that the information will produce the topology of the tree for the desired evolutionary model [22]. These results confirm and validate the direct colony PCR method to be applied as a reliable tool for the identification of bacterial fish pathogens in aquaculture. Although this method has already been used in previous studies for different purposes [14] [23], the present study represents the first practical application for the diagnosis of aquaculture diseases, a field lacking in terms of technological advancement.

Table 4. Cost analysis per sample for bacterial identification, performed in university laboratory already equipped.

Standard PCR Direct colony PCR

Steps U$ Time U$ Time

Bacterial isolation on plate 0.31 24 - 72 h 0.31 24 - 72 h

Replication in broth 0.41 24 - 48 h - -

DNA extraction 5.6 1 - 3 h - -

PCR 2.52 3 h 2.52 3 h

Electrophoresis 0.27 1.5 h 0.27 1.5 h

PCR product purification 2.54 1 h - -

16S rRNA sequencing 5.0 24 h 5.0 24 h

Nucleotide analysis - 1 h - 1 h

Overall 16.65 4 - 7 days 8.1 3 - 5 days

*Isolation times vary depending on the species being cultured.

Table 5. Advantages and disadvantages of each method for aquaculture diagnosis.

Classical microbiology Standard PCR Colony PCR

Conclusive diagnosis, faster than Conclusive diagnosis; 51% more economical; Advantages Less technicization the classical Microbiology 24 - 48 h faster than standard PCR.

Inconclusive and time More costly; 1% to 3% can fail; Disadvantages consuming diagnosis It depends on bacterial culture Still depends bacterial culture

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Figure 2. Relationship among different bacteria species using 16S rRNA gene sequences, inferred by maximum-likelihood method. The phylogenetic diagram shows the correct clustering of related fish bacteria isolated in the present study.

3.2. The Analysis of the Common Bacterial Fish Pathogens Direct colony PCR, combined with gene sequencing, was able to detect the most common and important pathogens in aquaculture, such as Aeromonas hydrophila, Aeromonas veronii, Aeromonas jandaei, Streptococcus agalactiae, Streptococcus iniae, Streptococcus dysgalactiae, Edwardsiella tarda, Pseudomonas sp., Lactococcus garvieae, Citrobacter freundii, Plesiomonas shigelloides, and Enterococcus sp. As shown in Figure 3, genera related to pathogenic bacteria and with higher frequency among 178 bacterial isolates of this study were Aeromonas (31%), Lactococcus (23%), Enterococcus (22%), Streptococcus (20%), Pseudomonas (11%), Citrobacter (6%), Edwardsiella (5%), Acinetobacter (3%), Enterobacter (2%), Plesiomo- nas (1%) and Weissela (1%). Of the 43 Aeromonas isolates, 53% were identified as A. hydrophila by 16S rRNA gene sequencing. This result is in accordance with previous reports that found this species to be predominant [24]. In turn, A. veronii corresponded to 40% of the isolates. The seasonality was also observed in the present study: at higher tempera- tures (Spring/Summer) there were higher isolation rates of these pathogens [25], which causes hemorrhagic septicemia, characterized by small superficial lesions, focal hemorrhages, ulcers, abscesses, and abdominal disten- sion. Internally, there can be ascitic fluid accumulation, anemia, and lesions in the liver and kidneys [26]. For the genus Lactococcus, the emerging species L. garvieae corresponded to 52% of the total 29 isolates of this genus, followed by L. lactis with 41% incidence in fish originating from the states included in the present study, with higher incidence in P. reticulatum. The species L. garvieae has been isolated from several fish species worldwide, namely in Japan [27], South Africa [28], Europe [29], and Brazil. Its first outbreak was reported in 2009 [7]. Fish with lactococcal infection exhibit lethargy, anorexia, skin darkening and swim closer to the water surface [30], resulting in considerable economic losses, especially during the summer months when the water temperature increases [4]. Few studies report L. lactis as an opportunistic pathogen. However, L. lactis subsp. lactis has been responsible for a 100% loss of hybrid sturgeons (Huso huso × Acipenser ruthenus) in a fish farm in Taiwan, China [31].

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20 (%) 15

Bacterial genera Figure 3. Percentage of bacterial genera identified by 16S rRNA gene of the 178 isolates of this study distributed in the states of Mato Grosso do Sul, São Paulo, Paraná and Rio de Janeiro.

In the present study, 31 Enterococcus strains were isolated from skin and kidney samples. Of these, 55% were E. casseliflavus, 36% E. faecalis, 6% E.durans, and 3% E. sulfureus. The predominance of E. casseliflavus has also been observed among isolates from water and sediment, accounting for 66.7% of a total of 410 Enterococ- cus sp. isolates in Thailand [32]. Of the 27 Streptococcus strains originating from the states of Mato Grosso do Sul, Paraná, and São Paulo, 89% corresponded to S. agalactiae; this was previously observed by Netto et al. [33] and Figueiredo et al. [10]. Al- though infection by S. agalactiae is the main cause of losses in tilapia farming worldwide, this pathogen has also been isolated from “cachara” originating from Mato Grosso do Sul. S. agalactiae has been identified in several other fish species, such as Sparus auratus, Liza klunzingeri [34], and Pampusargenteus [35]. Infected fish have meningoencephalitis, exophthalmia, erratic swimming, mainly. The species P. putida (27%) and P. fulva (20%) were the predominant Pseudomonas species observed (n = 15). Eissa et al. [36] observed an incidence of 30.83% of Pseudomonas species in Nile tilapia in Egypt. Hussain [37] and Zorrilla et al. [38] reported 13.5%, and 9.7% incidence, respectively, of Pseudomonas species in marine fish, values that are similar to the 11% incidence found in the present study. P. fluorescens, P. angullisepti- ca, P. aeruginosa and P. putida were identified in various species of fish as causative agents of Pseudomonas septicemia. The disease is characterized by petechial hemorrhage, darkness of the skin, detached scales, abdominal ascitis and exophthalmia [39]. As the number of isolates from each region was dissimilar and low, it would not be advisable to determine a frequency profile of pathogens by location, neither the prevalence of bacterial genera by fish species, but we emphasize the importance of drawing a regional profile in aquaculture health monitoring programs and preven- tive management, therefore, in case of disease outbreak, treatment measures are different in each region, since factors such as light, water quality and soil contamination, quantity of parasites, management, etc are also pecu- liar to each locality.

4. Conclusion Direct colony PCR combined with 16S rRNA gene sequencing constitutes an efficient alternative for diagnosing bacterial fish diseases, with decreased cost and time compared with the classical methods used in Brazil, such as isolation, biochemical tests, and conventional PCR.

Acknowledgements The author wishes to thank the State of São Paulo Research Foundation (FAPESP-Process 2011/07951-5) for the financial support; the Aquaculture Center (CAUNESP/UNESP, Jaboticabal) and the Laboratory of Microbial and Plant Biochemistry, Technology Department (Laboratório de Bioquímica de Microrganismos e Plantas, FCAV/UNESP Jaboticabal), UNESP, for technical support; and Dr. Fabiana Garcia for donating the bacterial strains.

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Supplementary Data

GenBank Sample Fish Organ Molecular identification Location Time Molecular size (bp) accession numbers KJ560937 4n Tilapia Skin Edwardsiella tarda Nepean, Jaboticabal sp Spring 2013 868

KJ560938 T1.3a Tilapia Gills Edwardsiella tarda Porto Ferreira SP Spring 2013 825

KJ560939 2dp Tilapia Kidney Edwardsiella tarda Porto Ferreira SP Spring 2013 855

KJ560940 18FG Tilapia Skin Edwardsiella tarda Rio Paranapanema (SP/PR) Winter 2012 858

KJ560941 91 FG Tilapia Skin Edwardsiella tarda Rio Paranapanema (SP/PR) Winter 2012 860

KJ560942 8g Pacu Kidney Edwardsiella tarda Caunesp, Jaboticabal, SP Spring 2013 847

KJ560943 3dp Tilapia Kidney Edwardsiella tarda Porto Ferreira SP Spring 2013 873

KJ560944 45MS Cachara Skin Enterobacter asburiae MS Winter 2012 851

KJ560945 47MS Cachara Kidney Kosakonia cowanii MS Winter 2012 857

KJ560946 48MS Cachara Kidney Enterobacter ludwigii MS Winter 2012 800

KJ560947 A77 Tilapia Kidney Enterobacter kobei Arealva SP Spring 2011 830

KJ560948 A79 Tilapia Kidney Enterobacter kobei Arealva SP Spring 2011 853

KJ560949 A70 Tilapia Skin Enterobacter ludwigii Arealva SP Spring 2011 855

KJ560950 A1 Tambaqu Skin Enterococcus casseliflavus Caunesp, Jaboticabal SP Spring 2011 859

KJ560951 A8 Tambaqui Skin Enterococcus casseliflavus Caunesp, Jaboticabal SP Spring 2011 857

KJ560952 A5 Tambaqui Skin Enterococcus casseliflavus Caunesp, Jaboticabal SP Spring 2011 869

KJ560953 A9 Tambaqui Skin Enterococcus casseliflavus Caunesp, Jaboticabal SP Spring 2011 860

KJ560954 A2 Tambaqui Skin Enterococcus casseliflavus Caunesp, Jaboticabal SP Spring 2011 866

KJ560955 A6 Tambaqui Skin Enterococcus casseliflavus Caunesp, Jaboticabal SP Spring 2011 841

KJ560956 A10 Tambaqui Skin Enterococcus casseliflavus Caunesp, Jaboticabal SP Spring 2011 862

KJ560957 A7 Tambaqui Skin Enterococcus casseliflavus Caunesp, Jaboticabal SP Spring 2011 862

KJ560958 A14 Tilapia Skin Enterococcus casseliflavus Caunesp, Jaboticabal SP Spring 2011 856

KJ560959 P Tilapia Brain Enterococcus casseliflavus Itambaracá PR Summer 2010 853

KJ560960 S27 Tilapia Kidney Enterococcus casseliflavus Caunesp, Jaboticabal Winter 2011 879 KJ560961 S22 Tilapia Skin Enterococcus casseliflavus Caunesp, Jaboticabal SP Winter 2011 871

KJ560962 S28 Tilapia Brânquia Enterococcus casseliflavus Caunesp, Jaboticabal Winter 2011 876

419 F. A. Sebastião et al.

Continued

KJ560963 S21 Tilapia Skin Enterococcus casseliflavus Caunesp, Jaboticabal SP Winter 2011 871

KJ560964 S19 Tilapia Skin Enterococcus casseliflavus Caunesp, Jaboticabal SP Winter 2011 867

KJ560965 S25 Tilapia Skin Enterococcus casseliflavus Caunesp, Jaboticabal SP Winter 2011 872

KJ560966 5MS Cachara Kidney Enterococcus durans MS Spring 2012 840

KJ560967 S9 Tilapia Skin Enterococcus durans Arealva SP Spring 2011 874

KJ560968 3 MS Cachara Kidney Enterococcus faecalis MS Spring 2012 854

KJ560969 4MS Cachara Kidney Enterococcus faecalis MS Spring 2012 840

KJ560970 7MS Cachara Kidney Enterococcus faecalis MS Spring 2012 846

KJ560971 8MS Cachara Kidney Enterococcus faecalis MS Spring 2012 837

KJ560972 10MS Cachara Kidney Enterococcus faecalis MS Spring 2012 852

KJ560973 13ms Cachara Kidney Enterococcus faecalis MS Spring 2012 849

KJ560974 28ms Cachara Kidney Enterococcus faecalis MS Spring 2012 873

KJ560975 42ms Cachara Kidney Enterococcus faecalis MS Spring 2012 838

KJ560976 43ms Cachara Kidney Enterococcus faecalis MS Spring 2012 864

KJ560977 37ms Cachara Kidney Enterococcus faecalis MS Spring 2012 874

KJ560978 S14 Tilapia Skin Enterococcus faecalis Arealva SP Winter 2011 864

KJ560979 26ms Cachara Kidney Enterococcus sulfureus MS Spring 2012 850

KJ560980 20b dp Tilapia Gills Klebsiella pneumoniae Porto Ferreira SP Fall 2014 819

KJ560981 46MS Cachara Skin Klebsiella pneumoniae MS Spring 2012 855

KJ560982 B1 Tilapia Skin Kurthia gibsonii Arealva SP Spring 2011 837

KJ560983 A71 Tilapia Skin Lactococcus garviae Arealva SP Winter 2011 834

KJ560984 A74 Tilapia Kidney Lactococcus garviae Arealva SP Winter 2011 855

KJ560985 497 FG Tilapia Brain Lactococcus garviae Rio Paranapanema (SP/PR) Spring 2012 789

KJ560986 491 FG Tilapia Brain Lactococcus garviae Rio Paranapanema (SP/PR) Spring 2012 843

KJ560987 Zo1 Tilapia Kidney Lactococcus garviae Guaíra SP Fall 2014 865

KJ560988 Zo2 Tilapia Kidney Lactococcus garviae Guaíra SP Fall 2014 866

KJ560989 6n Tilapia Skin Lactococcus garviae Nepean, Jaboticabal SP Spring 2013 875

KJ560990 A62 Tilapia Skin Lactococcus garviae Arealva SP Winter 2011 845

KJ560991 15ms Cachara Kidney Lactococcus garviae MS Spring 2012 846

KJ560992 14ms Cachara Kidney Lactococcus garviae MS Spring 2012 853

KJ560993 31ms Cachara Kidney Lactococcus garviae MS Spring 2012 866

KJ560994 33ms Cachara Kidney Lactococcus garviae MS Spring 2012 853

KJ560995 36ms Cachara Kidney Lactococcus garviae MS Spring 2012 810

KJ560996 52MS Cachara Brain Lactococcus garviae MS Spring 2012 810

KJ560997 S11 Tilapia Skin Lactococcus garviae Arealva SP Winter 2011 799

KJ560998 9MS Cachara Brain Lactococcus lactis subsp. cremoris MS Spring 2012 807

420 F. A. Sebastião et al.

Continued

KJ560999 499 FG Tilapia Brain Lactococcus lactis subsp. cremoris Rio Paranapanema (SP/PR) Spring 2012 799

KJ561000 S17 Tilapia Skin Lactococcus lactis subsp. lactis Caunesp, Jaboticabal SP Winter 2011 869

KJ561001 17ms Cachara Kidney Lactococcus lactis subsp. lactis MS Spring 2012 852

KJ561002 18ms Cachara Kidney Lactococcus lactis subsp. Lactis MS Spring 2012 861

KJ561003 20ms Cachara Kidney Citrobacter freundii MS Spring 2012 842

KJ561004 24ms Cachara Kidney Lactococcus lactis subsp. Lactis MS Spring 2012 858

KJ561005 500 FG Tilapia Brain Lactococcus lactis subsp. lactis Rio Paranapanema (SP/PR) Spring 2012 829

KJ561006 39ms Cachara Kidney Lactococcus lactis subsp. Lactis MS Spring 2012 832

KJ561007 41ms Cachara Kidney Lactococcus lactis subsp. lactis MS Spring 2012 836

KJ561008 111 FG Tilapia Brain Lactococcus lactis subsp. lactis Rio Paranapanema (SP/PR) Spring 2012 845

KJ561009 498 FG Tilapia Brain Lactococcus lactis subsp. lactis Rio Paranapanema (SP/PR) Spring 2012 858

KJ561010 S8 Tambaqui Skin Lactococcus lactis subsp. lactis Arealva SP Winter 2011 862

KJ561011 A15 Tilapia Brain Lactococcus raffinolactis Caunesp, Jaboticabal SP Winter 2011 859

KJ561012 505 FG Tilapia Brain Lactococcus raffinolactis Rio Paranapanema (SP/PR) Spring 2012 839

KJ561013 A3 Tambaqui Skin Leucobacter aridicollis Caunesp, Jaboticabal SP Winter 2011 830

KJ561014 1sil Pacu Kidney Aeromonas hydrophila Caunesp, Jaboticabal SP Fall 2014 865

KJ561015 5sil Pacu Kidney Aeromonas hydrophila Caunesp, Jaboticabal SP Fall 2014 877

KJ561016 10dp Tilapia Skin Aeromonas hydrophila Porto Ferreira SP Spring 2013 866

KJ561017 9dp Tilapia Gills Aeromonas hydrophila Porto Ferreira SP Spring 2013 867

KJ561018 A129 Tilapia Kidney Aeromonas hydrophila Arealva SP Winter 2011 858

KJ561019 Atcc7966 Tilapia Enviroment Aeromonas hydrophila RJ Summer 2011 867

KJ561020 A130 Tilapia Skin Aeromonas hydrophila Arealva SP Winter 2011 846

KJ561021 A122 Pintado Skin Aeromonas hydrophila Arealva SP Winter 2011 846

KJ561022 A133 Tilapia Skin Aeromonas hydrophila Arealva SP Winter 2011 851

KJ561023 41FG Tilapia Kidney Aeromonas hydrophila Rio Paranapanema (SP/PR) Spring 2012 861

KJ561024 A128 Tilapia Skin Aeromonas hydrophila Arealva SP Winter 2011 855

KJ561025 A135 Carpa Skin Aeromonas hydrophila RJ Summer 2011 862

KJ561026 117 FG Tilapia Kidney Aeromonas hydrophila Rio Paranapanema (SP/PR) Spring 2012 854

KJ561027 120 FG Tilapia Kidney Aeromonas hydrophila Rio Paranapanema (SP/PR) Spring 2012 821

KJ561028 121 FG Tilapia Kidney Aeromonas hydrophila Rio Paranapanema (SP/PR) Spring 2012 817

KJ561029 125 FG Tilapia Kidney Aeromonas hydrophila Rio Paranapanema (SP/PR) Spring 2012 839

KJ561030 126 FG Tilapia Kidney Aeromonas hydrophila Rio Paranapanema (SP/PR) Spring 2012 694

KJ561031 128 FG Tilapia Kidney Aeromonas hydrophila Rio Paranapanema (SP/PR) Spring 2012 656

KJ561032 14dp Tilapia Kidney Aeromonas jandaei Porto Ferreira SP Spring 2013 864

KJ561033 A124 Tilapia Brain Aeromonas jandaei Arealva SP Winter 2011 865

KJ561034 A110 Pintado Skin Aeromonas punctata Arealva SP Winter 2011 843

421 F. A. Sebastião et al.

Continued

KJ561035 7sil Pacu Kidney Aeromonas veronii Caunesp, Jaboticabal SP Fall 2014 750

KJ561036 an Tilapia Kidney Aeromonas veronii Nepean, Jaboticabal SP Fall 2014 806

KJ561037 6sil Pacu Kidney Aeromonas veronii Caunesp, Jaboticabal SP Fall 2014 870

KJ561038 5n Tilapia Skin Aeromonas veronii Nepean, Jaboticabal SP Spring 2013 880

KJ561039 1dp Tilapia Kidney Aeromonas veronii Porto Ferreira SP Spring 2013 779

KJ561040 A107 Pintado Brain Aeromonas veronii Arealva SP Winter 2011 859

KJ561041 A115 Pintado Brain Aeromonas veronii Arealva SP Winter 2011 835

KJ561042 A131 Tilapia Brain Aeromonas veronii Arealva SP Winter 2011 854

KJ561043 A119 Pintado Brain Aeromonas veronii Arealva SP Winter 2011 821

KJ561044 A116 Pintado Brain Aeromonas veronii Arealva SP Winter 2011 839

KJ561045 A113 Pintado Kidney Aeromonas veronii Arealva SP Winter 2011 833

KJ561046 A109 Pintado Brain Aeromonas veronii Arealva SP Winter 2011 869

KJ561047 A134 Carpa Skin Aeromonas veronii RJ Summer 2011 855

KJ561048 A136 Carpa Skin Aeromonas veronii RJ Summer 2011 853

KJ561049 A112 Pintado Muco Aeromonas veronii Arealva SP Winter 2011 860

KJ561050 124 FG Tilapia Brain Streptococcus agalactiae Rio Paranapanema (SP/PR) Spring 2012 806

KJ561051 Zo5 Tilapia Brain Streptococcus agalactiae Guaíra SP Fall 2014 850

KJ561052 Zo9s Tilapia Brain Streptococcus agalactiae Guaíra SP Fall 2014 866

KJ561053 78 FG Tilapia Brain Streptococcus agalactiae Rio Paranapanema (SP/PR) Spring 2012 854

KJ561054 99 FG Tilapia Brain Streptococcus agalactiae Rio Paranapanema (SP/PR) Spring 2012 865

KJ561055 103 FG Tilapia Brain Streptococcus agalactiae Rio Paranapanema (SP/PR) Spring 2012 865

KJ561056 100 FG Tilapia Brain Streptococcus agalactiae Rio Paranapanema (SP/PR) Spring 2012 863

KJ561057 104 FG Tilapia Brain Streptococcus agalactiae Rio Paranapanema (SP/PR) Spring 2012 859

KJ561058 76 FG Tilapia Brain Streptococcus agalactiae Rio Paranapanema (SP/PR) Spring 2012 871

KJ561059 105 FG Tilapia Brain Streptococcus agalactiae Rio Paranapanema (SP/PR) Spring 2012 864

KJ561060 77 FG Tilapia Brain Streptococcus agalactiae Rio Paranapanema (SP/PR) Spring 2012 866

KJ561061 106 FG Tilapia Brain Streptococcus agalactiae Rio Paranapanema (SP/PR) Spring 2012 865

KJ561062 102 FG Tilapia Brain Streptococcus agalactiae Rio Paranapanema (SP/PR) Spring 2012 853

KJ561063 18P Tilapia Fígado Streptococcus agalactiae Itambaracá PR Fall 2010 840

KJ561064 74P Tilapia Brain Streptococcus agalactiae Itambaracá PR Fall 2011 789

KJ561065 26P Tilapia Kidney Streptococcus agalactiae Itambaracá PR Fall 2011 855

KJ561066 45P Tilapia Kidney Streptococcus agalactiae Itambaracá PR Winter 2011 831

KJ561067 36P Tilapia Fígado Streptococcus agalactiae Itambaracá PR Summer 2011 853

KJ561068 43P Tilapia Brain Streptococcus agalactiae Itambaracá PR Winter 2011 603

KJ561069 110 FG Tilapia Brain Streptococcus agalactiae Rio Paranapanema (SP/PR) Spring 2012 422

KJ561070 M Tilapia Brain Streptococcus agalactiae Itambaracá PR Fall 2011 853

422 F. A. Sebastião et al.

Continued

KJ561071 64P Tilapia Brain Streptococcus agalactiae Itambaracá PR Winter 2011 681

KJ561072 112 FG Tilapia Brain Streptococcus agalactiae Rio Paranapanema (SP/PR) Spring 2012 846

KJ561073 Zo4 Tilapia Brain Streptococcus iniae Guaíra SP Fall 2014 839

KJ561074 Zo7 Tilapia Brain Streptococcus iniae Guaíra SP Fall 2014 839

KJ561075 79 FG Tilapia Brain Streptococcus iniae Rio Paranapanema (SP/PR) Summer 2012 859 Reservatório de Ilha Sol- KJ561076 81 FG Tilapia Brain Streptococcus iniae Summer 2012 862 teira, rio Paraná SP KJ561077 40ms Cachara Kidney Streptococcus dysgalactiae MS Spring 2012 846

KJ561078 52 P Tilapia Kidney Weissella confusa Itambaracá PR Summer 2011 852

KJ561079 23FG Tilapia Skin Acinetobacter johnsonii Rio Paranapanema (SP/PR) Spring 2012 843

KJ561080 C1 Carpa Skin Acinetobacter tjernbergiae RJ Summer 2011 819

KJ561081 30 AM FG Tilapia Skin Acinetobacter radioresistens Rio Paranapanema (SP/PR) Spring 2012 850

KJ561082 84AM FG Tilapia Skin Acinetobacter ursingii Rio Paranapanema (SP/PR) Spring 2012 849

KJ561083 96AM FG Tilapia Skin Agrobacterium tumefaciens Rio Paranapanema (SP/PR) Spring 2012 799

KJ561084 69ROSA FG Tilapia Skin Arthrobacter globiformis Rio Paranapanema (SP/PR) Spring 2012 830

KJ561085 57MS Cachara Skin Bacillus stratoSPhericus MS Spring 2012 828

KJ561086 22ms Cachara Kidney Brevibacillus agri MS Spring 2012 833

KJ561087 23ms Cachara Kidney Brevibacillus agri MS Spring 2012 727

KJ561088 16ms Cachara Skin Carnobacterium divergens MS Spring 2012 872

KJ561089 11dp Tilapia Skin Citrobacter freundii Porto Ferreira SP Spring 2013 867

KJ561090 A108 Pintado Brain Citrobacter freundii Arealva SP Winter 2011 856

KJ561091 44 MS Cachara Kidney Citrobacter freundii MS Spring 2012 850

KJ561092 54MS Cachara Kidney Citrobacter freundii MS Spring 2012 800

KJ561093 1g Pacu Kidney Citrobacter freundii Caunesp, Jaboticabal SP Spring 2013 779

KJ561094 A99 Catfish Baço Citrobacter murliniae Dourados ms Winter 2011 860

KJ561095 115 FG Tilapia Skin Pseudomonas chlororaphis Rio Paranapanema (SP/PR) Spring 2012 752

KJ561096 A78 Tilapia Skin Pseudomonas fulva Arealva SP Winter 2011 845

KJ561097 A75 Tilapia Kidney Pseudomonas fulva Arealva SP Winter 2011 813

KJ561098 116 FG Tilapia Skin Pseudomonas fulva Rio Paranapanema (SP/PR) Spring 2012 826

KJ561099 114 FG Tilapia Skin Pseudomonas libanensis Rio Paranapanema (SP/PR) Spring 2012 827

KJ561100 93FG Tilapia Kidney Pseudomonas monteilii Rio Paranapanema (SP/PR) Spring 2012 846

KJ561101 A76 Tilapia Skin Pseudomonas mosselii Arealva SP Winter 2011 844

KJ561102 A82 Tilapia Skin Pseudomonas mosselii Arealva SP Winter 2011 818

KJ561103 A66 Tambaqui Skin Pseudomonas nitroreducens Arealva SP Winter 2011 821

KJ561104 94FG Tilapia Kidney Pseudomonas plecoglissida Rio Paranapanema (SP/PR) Spring 2012 854

KJ561105 4sil Pacu Gills Pseudomonas putida Caunesp, Jaboticabal SP Fall 2014 856

KJ561106 2sil Pacu Gills Pseudomonas putida Caunesp, Jaboticabal SP Fall 2014 850

423 F. A. Sebastião et al.

Continued

KJ561107 T5-1 Tilapia Baço Pseudomonas putida Porto Ferreira SP Spring 2013 862

KJ561108 3sil Pacu Skin Pseudomonas putida Caunesp, Jaboticabal SP Fall 2014 690

KJ561109 49MS Cachara Skin Pseudomonas stutzeri MS Spring 2012 850

KJ561110 49AM FG Tilapia Skin Stenotrophomonas chelatiphaga Rio Paranapanema (SP/PR) Spring 2012 858

KJ561111 22FG Tilapia Skin Stenotrophomonas maltophilia Rio Paranapanema (SP/PR) Spring 2012 867

KJ561112 T3.5b Tilapia Skin Plesiomonas shigelloides Porto Ferreira SP Spring 2013 864

KJ561113 A132 Tilapia Skin Comamonas testosteroni Arealva SP Winter 2011 849

424